Modash MCP Server for Pydantic AI 11 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Modash through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Modash "
"(11 tools)."
),
)
result = await agent.run(
"What tools are available in Modash?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Modash MCP Server
Connect Modash to your AI agent to discover the perfect creators for your brand. Access a database of 350M+ influencers and get deep audience analytics through natural conversation.
Pydantic AI validates every Modash tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Influencer Search — Find creators based on followers, engagement rate, and location across major platforms.
- Audience Analytics — Get detailed reports on audience demographics, location, and authenticity.
- Platform Coverage — Seamlessly switch between Instagram, TikTok, and YouTube research.
- Dictionary Access — Easily find IDs for locations, interests, and brands to refine your searches.
- Real-time Data — Fetch the latest metrics and posts directly from influencer profiles.
The Modash MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Modash to Pydantic AI via MCP
Follow these steps to integrate the Modash MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 11 tools from Modash with type-safe schemas
Why Use Pydantic AI with the Modash MCP Server
Pydantic AI provides unique advantages when paired with Modash through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Modash integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Modash connection logic from agent behavior for testable, maintainable code
Modash + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Modash MCP Server delivers measurable value.
Type-safe data pipelines: query Modash with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Modash tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Modash and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Modash responses and write comprehensive agent tests
Modash MCP Tools for Pydantic AI (11)
These 11 tools become available when you connect Modash to Pydantic AI via MCP:
get_instagram_report
Get deep analytics for an Instagram profile
get_raw_profile
Get real-time, unfiltered profile data
get_tiktok_report
Get analytics for a TikTok profile
get_youtube_report
Get analytics for a YouTube channel
list_brands
Search for brand IDs
list_interests
Search for interest IDs
list_languages
Search for language IDs
list_locations
Search for location IDs
search_instagram
Search for Instagram influencers
search_tiktok
Search for TikTok influencers
search_youtube
Search for YouTube channels
Example Prompts for Modash in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Modash immediately.
"Search for Instagram influencers with 50k-100k followers in London."
"Get an audience report for the TikTok user @traveler_vlog."
"List all interest categories available for YouTube search."
Troubleshooting Modash MCP Server with Pydantic AI
Common issues when connecting Modash to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiModash + Pydantic AI FAQ
Common questions about integrating Modash MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Modash with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Modash to Pydantic AI
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.